|
|
| Acesso ao texto completo restrito à biblioteca da Embrapa Arroz e Feijão. Para informações adicionais entre em contato com cnpaf.biblioteca@embrapa.br. |
Registro Completo |
Biblioteca(s): |
Embrapa Arroz e Feijão. |
Data corrente: |
19/06/2017 |
Data da última atualização: |
20/06/2017 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
HEINEMANN, A. B.; RAMIREZ-VILLEGAS, J.; STONE, L. F.; DIDONET, A. D. |
Afiliação: |
ALEXANDRE BRYAN HEINEMANN, CNPAF; JULIAN RAMIREZ-VILLEGAS, CIAT; LUIS FERNANDO STONE, CNPAF; AGOSTINHO DIRCEU DIDONET, CNPAF. |
Título: |
Climate change determined drought stress profiles in rainfed common bean production systems in Brazil. |
Ano de publicação: |
2017 |
Fonte/Imprenta: |
Agricultural and Forest Meteorology, v. 246, p. 64-77, 2017. |
ISSN: |
0168-1923 |
DOI: |
10.1016/j.agrformet.2017.06.005 |
Idioma: |
Inglês |
Conteúdo: |
Reductions in agricultural productivity with consequences for food security associated to climate change are expected in the absence of adaptation. For common beans, across South America, a decrease in climatic suitability has been projected, with heat and drought stresses being the key drivers for such suitability reductions. Breeding programs will play an important role in the adaptation of common beans to the changing climates. However, breeding targets may vary as climate changes during the 21st century. Here, we assess historical and future (2030) probabilities of occurrence, intensity and impact of seasonal variations of drought stress, which is the most important stress for common beans in the Goiás state. We focus on two rainfed (wet and dry) target population environments (TPEs), which encompass ca. 62% of the bean cropped area in the state for 2016, and address potential breeding implications of future projected changes. The analysis revealed two environment groups for both TPEs (highly favorable environment and favorable environment), and four drought stress profiles within these environmental groups (drought stress free, reproductive stress, terminal stress, and joint reproductive-terminal stress) across all climate and management (cultivars and sowing dates) scenarios. Results suggest that, with respect to the historical (1980?2005) period, climate change will make drought more frequent, but less severe, across the region. For the dry TPE, the probability of occurrence of drought stress situations (reproductive and/or terminal) changes from 29.6% (baseline) to ca. 70% (2030, RCP [Representative Concentrations Pathway] 8.5), whereas for the wet TPE, it increases from 16% (baseline) to ca. 43% (2030, RCP 8.5). Results are consistent across RCPs, although benefits from stringent (RCP 2.6) mitigation are evident. We conclude that drought tailoring under climate change is needed for the Embrapa dry bean breeding program MenosReductions in agricultural productivity with consequences for food security associated to climate change are expected in the absence of adaptation. For common beans, across South America, a decrease in climatic suitability has been projected, with heat and drought stresses being the key drivers for such suitability reductions. Breeding programs will play an important role in the adaptation of common beans to the changing climates. However, breeding targets may vary as climate changes during the 21st century. Here, we assess historical and future (2030) probabilities of occurrence, intensity and impact of seasonal variations of drought stress, which is the most important stress for common beans in the Goiás state. We focus on two rainfed (wet and dry) target population environments (TPEs), which encompass ca. 62% of the bean cropped area in the state for 2016, and address potential breeding implications of future projected changes. The analysis revealed two environment groups for both TPEs (highly favorable environment and favorable environment), and four drought stress profiles within these environmental groups (drought stress free, reproductive stress, terminal stress, and joint reproductive-terminal stress) across all climate and management (cultivars and sowing dates) scenarios. Results suggest that, with respect to the historical (1980?2005) period, climate change will make drought more frequent, but less severe, across the region. For the dry TPE, the probability of occ... Mostrar Tudo |
Palavras-Chave: |
Melhoramento genético; Mitigation measures. |
Thesagro: |
Feijão; Phaseolus vulgaris; Resistencia a seca; Resistencia a temperatura. |
Thesaurus Nal: |
Beans; Climate change; Simulation models; Water stress. |
Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
Marc: |
LEADER 02877naa a2200301 a 4500 001 2071093 005 2017-06-20 008 2017 bl uuuu u00u1 u #d 022 $a0168-1923 024 7 $a10.1016/j.agrformet.2017.06.005$2DOI 100 1 $aHEINEMANN, A. B. 245 $aClimate change determined drought stress profiles in rainfed common bean production systems in Brazil.$h[electronic resource] 260 $c2017 520 $aReductions in agricultural productivity with consequences for food security associated to climate change are expected in the absence of adaptation. For common beans, across South America, a decrease in climatic suitability has been projected, with heat and drought stresses being the key drivers for such suitability reductions. Breeding programs will play an important role in the adaptation of common beans to the changing climates. However, breeding targets may vary as climate changes during the 21st century. Here, we assess historical and future (2030) probabilities of occurrence, intensity and impact of seasonal variations of drought stress, which is the most important stress for common beans in the Goiás state. We focus on two rainfed (wet and dry) target population environments (TPEs), which encompass ca. 62% of the bean cropped area in the state for 2016, and address potential breeding implications of future projected changes. The analysis revealed two environment groups for both TPEs (highly favorable environment and favorable environment), and four drought stress profiles within these environmental groups (drought stress free, reproductive stress, terminal stress, and joint reproductive-terminal stress) across all climate and management (cultivars and sowing dates) scenarios. Results suggest that, with respect to the historical (1980?2005) period, climate change will make drought more frequent, but less severe, across the region. For the dry TPE, the probability of occurrence of drought stress situations (reproductive and/or terminal) changes from 29.6% (baseline) to ca. 70% (2030, RCP [Representative Concentrations Pathway] 8.5), whereas for the wet TPE, it increases from 16% (baseline) to ca. 43% (2030, RCP 8.5). Results are consistent across RCPs, although benefits from stringent (RCP 2.6) mitigation are evident. We conclude that drought tailoring under climate change is needed for the Embrapa dry bean breeding program 650 $aBeans 650 $aClimate change 650 $aSimulation models 650 $aWater stress 650 $aFeijão 650 $aPhaseolus vulgaris 650 $aResistencia a seca 650 $aResistencia a temperatura 653 $aMelhoramento genético 653 $aMitigation measures 700 1 $aRAMIREZ-VILLEGAS, J. 700 1 $aSTONE, L. F. 700 1 $aDIDONET, A. D. 773 $tAgricultural and Forest Meteorology$gv. 246, p. 64-77, 2017.
Download
Esconder MarcMostrar Marc Completo |
Registro original: |
Embrapa Arroz e Feijão (CNPAF) |
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
URL |
Voltar
|
|
| Acesso ao texto completo restrito à biblioteca da Embrapa Amazônia Oriental. Para informações adicionais entre em contato com cpatu.biblioteca@embrapa.br. |
Registro Completo
Biblioteca(s): |
Embrapa Amazônia Oriental. |
Data corrente: |
25/10/2022 |
Data da última atualização: |
25/10/2022 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 2 |
Autoria: |
BRICEÑO CASTILLO, G. V.; FREITAS, L. J. M. de; CORDEIRO, V. A.; ORELLANA, J. B. P.; REATEGUI-BETANCOURT, J. L.; NAGY, L.; MATRICARDI, E. A. T. |
Afiliação: |
GUIDO VICENTE BRICEÑO CASTILLO, UNIVERSIDADE DE BRASÍLIA; LUCAS JOSE MAZZEI DE FREITAS, CPATU; VICTOR ALMEIDA CORDEIRO, UNIVERSIDADE DE BRASÍLIA; JORGE BRENO PALHETA ORELLANA, UNIVERSIDADE DE BRASÍLIA; JORGE LUIS REATEGUI-BETANCOURT, UNIVERSIDADE DE BRASÍLIA; LASZLO NAGY, UNIVERSIDADE ESTADUAL DE CAMPINAS; ERALDO APARECIDO TRONDOLI MATRICARDI, UNIVERSIDADE DE BRASÍLIA. |
Título: |
Assessment of selective logging impacts using UAV, Landsat, and Sentinel data in the Brazilian Amazon rainforest. |
Ano de publicação: |
2022 |
Fonte/Imprenta: |
Journal of Applied Remote Sensing, v. 16, n. 1, 014526, Mar. 2022. |
DOI: |
https://doi.org/10.1117/1.JRS.16.014526 |
Idioma: |
Inglês |
Conteúdo: |
Several studies have assessed forest disturbance in tropical forests using Landsat imagery. However, the spatial resolution (30 m) of Landsat images has often been considered too coarse to accurately detect the extent and impacts of selective logging. The Sentinel-2 satellite launched in 2015 has been providing images at spatial resolutions of 10 to 20 m and those images have shown an improved potential for detecting forest disturbances in tropical regions. We compared Landsat-8 and Sentinel-2 imagery for detecting selective logging in a rain forest site in the Brazilian Amazon. The aerosol-free modified soil adjusted vegetation index (MSAVI_af) was retrieved from the satellite images acquired in August 2020 immediately following logging. A robust reference dataset of very-high-resolution imagery (0.5 m) acquired using a complementary metal oxide semiconductor sensor (visible bands) onboard of an unmanned aerial vehicle was used to image the area of interest and a map derived from it was used to assess the classification accuracies made using satellite-derived data. The overall accuracy of the classified Sentinel-2 and Landsat-8 images varied between 54% and 83%, depending on the applied classification parameters for distinguishing undisturbed from disturbed forest canopy. Images acquired using the UAV allowed us to detect subtle impacts of canopy openings by selective logging activities. Images acquired using the UAV allowed the detection of small canopy openings, but not Sentinel-2 or Landsat-8. Sentinel-2 provided more details of canopy disturbances than Landsat image. Our classification approach is fully implementable on the Google Earth Engine platform and is a promising technique to monitor selective logging impacts in tropical forests. MenosSeveral studies have assessed forest disturbance in tropical forests using Landsat imagery. However, the spatial resolution (30 m) of Landsat images has often been considered too coarse to accurately detect the extent and impacts of selective logging. The Sentinel-2 satellite launched in 2015 has been providing images at spatial resolutions of 10 to 20 m and those images have shown an improved potential for detecting forest disturbances in tropical regions. We compared Landsat-8 and Sentinel-2 imagery for detecting selective logging in a rain forest site in the Brazilian Amazon. The aerosol-free modified soil adjusted vegetation index (MSAVI_af) was retrieved from the satellite images acquired in August 2020 immediately following logging. A robust reference dataset of very-high-resolution imagery (0.5 m) acquired using a complementary metal oxide semiconductor sensor (visible bands) onboard of an unmanned aerial vehicle was used to image the area of interest and a map derived from it was used to assess the classification accuracies made using satellite-derived data. The overall accuracy of the classified Sentinel-2 and Landsat-8 images varied between 54% and 83%, depending on the applied classification parameters for distinguishing undisturbed from disturbed forest canopy. Images acquired using the UAV allowed us to detect subtle impacts of canopy openings by selective logging activities. Images acquired using the UAV allowed the detection of small canopy openings, but not S... Mostrar Tudo |
Palavras-Chave: |
Drone; Imagem de satélite; Veículo aéreo não tripulado. |
Thesagro: |
Degradação Ambiental; Floresta Tropical; Impacto Ambiental. |
Thesaurus NAL: |
Unmanned aerial vehicles. |
Categoria do assunto: |
K Ciência Florestal e Produtos de Origem Vegetal |
Marc: |
LEADER 02732naa a2200289 a 4500 001 2147739 005 2022-10-25 008 2022 bl uuuu u00u1 u #d 024 7 $ahttps://doi.org/10.1117/1.JRS.16.014526$2DOI 100 1 $aBRICEÑO CASTILLO, G. V. 245 $aAssessment of selective logging impacts using UAV, Landsat, and Sentinel data in the Brazilian Amazon rainforest.$h[electronic resource] 260 $c2022 520 $aSeveral studies have assessed forest disturbance in tropical forests using Landsat imagery. However, the spatial resolution (30 m) of Landsat images has often been considered too coarse to accurately detect the extent and impacts of selective logging. The Sentinel-2 satellite launched in 2015 has been providing images at spatial resolutions of 10 to 20 m and those images have shown an improved potential for detecting forest disturbances in tropical regions. We compared Landsat-8 and Sentinel-2 imagery for detecting selective logging in a rain forest site in the Brazilian Amazon. The aerosol-free modified soil adjusted vegetation index (MSAVI_af) was retrieved from the satellite images acquired in August 2020 immediately following logging. A robust reference dataset of very-high-resolution imagery (0.5 m) acquired using a complementary metal oxide semiconductor sensor (visible bands) onboard of an unmanned aerial vehicle was used to image the area of interest and a map derived from it was used to assess the classification accuracies made using satellite-derived data. The overall accuracy of the classified Sentinel-2 and Landsat-8 images varied between 54% and 83%, depending on the applied classification parameters for distinguishing undisturbed from disturbed forest canopy. Images acquired using the UAV allowed us to detect subtle impacts of canopy openings by selective logging activities. Images acquired using the UAV allowed the detection of small canopy openings, but not Sentinel-2 or Landsat-8. Sentinel-2 provided more details of canopy disturbances than Landsat image. Our classification approach is fully implementable on the Google Earth Engine platform and is a promising technique to monitor selective logging impacts in tropical forests. 650 $aUnmanned aerial vehicles 650 $aDegradação Ambiental 650 $aFloresta Tropical 650 $aImpacto Ambiental 653 $aDrone 653 $aImagem de satélite 653 $aVeículo aéreo não tripulado 700 1 $aFREITAS, L. J. M. de 700 1 $aCORDEIRO, V. A. 700 1 $aORELLANA, J. B. P. 700 1 $aREATEGUI-BETANCOURT, J. L. 700 1 $aNAGY, L. 700 1 $aMATRICARDI, E. A. T. 773 $tJournal of Applied Remote Sensing$gv. 16, n. 1, 014526, Mar. 2022.
Download
Esconder MarcMostrar Marc Completo |
Registro original: |
Embrapa Amazônia Oriental (CPATU) |
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
Fechar
|
Expressão de busca inválida. Verifique!!! |
|
|